High-tech organizations maintain a portfolio of R&D projects that address problems with different levels of complexity. These projects use different strategies to search for technological solutions. Projects refining existing products, processes, and technologies, for instance, employ a local search strategy to improve performance, while projects developing new products, processes, and technologies employ a distant search strategy. However, projects can shift in their levels of complexity due to exogenous technological changes, and failure to change search strategy in turn can negatively impact project performance. This study first develops grounded theory via case studies to understand how high-tech organizations manage R&D projects when complexity shifts. The case data come from 142 informants in 12 R&D projects at three high-tech business units. A cross-case comparison shows that three interconnected mechanisms positioned at multiple levels within the organization enable high-tech organizations to identify such shifts and adjust the project's search. We refer to this strategy as responsive search. We then conduct agent-based simulation experiments to examine the conditions under which the responsive search outperforms other canonical search strategies. Overall, this study sheds light on the underexplored question of how to make mid-project corrections by effectively identifying and managing shifts in project complexity.